


import importlib
import os

import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry

from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem

from .utils import require_lza, require_zstandard
def      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     assert "mock" in _fsspec_registry
     assert "bz2" in _fsspec_registry
def      UpperCAmelCase__		():



     """simple docstring"""






     assert "mock" not in _fsspec_registry
     assert "bz2" in _fsspec_registry
def      UpperCAmelCase__		():



     """simple docstring"""






     snake_case											=							'''mock-s3-bucket'''
     snake_case											=							F'''s3://{mock_bucket}'''
     snake_case											=							extract_path_from_uri(UpperCamelCase_							)
     assert dataset_path.startswith('''s3://'''							) is False

     snake_case											=							'''./local/path'''
     snake_case											=							extract_path_from_uri(UpperCamelCase_							)
     assert dataset_path == new_dataset_path
def      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     snake_case											=							is_remote_filesystem(UpperCamelCase_							)
     assert is_remote is True

     snake_case											=							fsspec.filesystem('''file'''							)

     snake_case											=							is_remote_filesystem(UpperCamelCase_							)
     assert is_remote is False
@pytest.mark.parametrize('''compression_fs_class'''				,UpperCamelCase_							)
def      UpperCAmelCase__		(UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_							):



     """simple docstring"""






     snake_case											=							{'''gzip''': gz_file, '''xz''': xz_file, '''zstd''': zstd_file, '''bz2''': bza_file, '''lz4''': lza_file}
     snake_case											=							input_paths[compression_fs_class.protocol]
     if input_path is None:
          snake_case											=							F'''for \'{compression_fs_class.protocol}\' compression protocol, '''
          if compression_fs_class.protocol == "lz4":
               reason += require_lza.kwargs["reason"]
          elif compression_fs_class.protocol == "zstd":
               reason += require_zstandard.kwargs["reason"]
          pytest.skip(UpperCamelCase_							)
     snake_case											=							fsspec.filesystem(compression_fs_class.protocol				,fo=UpperCamelCase_							)
     assert isinstance(UpperCamelCase_				,UpperCamelCase_							)
     snake_case											=							os.path.basename(UpperCamelCase_							)
     snake_case											=							expected_filename[: expected_filename.rindex('''.'''							)]
     assert fs.glob('''*'''							) == [expected_filename]
     with fs.open(UpperCamelCase_				,'''r'''				,encoding='''utf-8'''							) as f, open(UpperCamelCase_				,encoding='''utf-8'''							) as expected_file:
          assert f.read() == expected_file.read()
@pytest.mark.parametrize('''protocol'''				,['''zip''', '''gzip''']							)
def      UpperCAmelCase__		(UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_							):



     """simple docstring"""






     snake_case											=							{'''zip''': zip_jsonl_path, '''gzip''': jsonl_gz_path}
     snake_case											=							compressed_file_paths[protocol]
     snake_case											=							'''dataset.jsonl'''
     snake_case											=							F'''{protocol}://{member_file_path}::{compressed_file_path}'''
     snake_case					,    *snake_case											=							fsspec.get_fs_token_paths(UpperCamelCase_							)
     assert fs.isfile(UpperCamelCase_							)
     assert not fs.isfile('''non_existing_''' + member_file_path							)
@pytest.mark.integration
def      UpperCAmelCase__		(UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_				,UpperCamelCase_							):



     """simple docstring"""






     snake_case											=							hf_api.dataset_info(UpperCamelCase_				,token=UpperCamelCase_							)
     snake_case											=							HfFileSystem(repo_info=UpperCamelCase_				,token=UpperCamelCase_							)
     assert sorted(hffs.glob('''*'''							)							) == [".gitattributes", "data"]
     assert hffs.isdir('''data'''							)
     assert hffs.isfile('''.gitattributes'''							) and hffs.isfile('''data/text_data.txt'''							)
     with open(UpperCamelCase_							) as f:
          assert hffs.open('''data/text_data.txt'''				,'''r'''							).read() == f.read()

def      UpperCAmelCase__		():



     """simple docstring"""






     snake_case											=							'''bz2'''

     # Import module
     import datasets.filesystems

     # Overwrite protocol and reload
     register_implementation(UpperCamelCase_				,UpperCamelCase_				,clobber=UpperCamelCase_							)
     with pytest.warns(UpperCamelCase_							) as warning_info:
          importlib.reload(datasets.filesystems							)

     assert len(UpperCamelCase_							) == 1
     assert (
         str(warning_info[0].message							)
         == F'''A filesystem protocol was already set for {protocol} and will be overwritten.'''
     )








import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
 from PIL import Image

 from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor

@require_vision
class     A__   (       unittest.TestCase      ):







    """simple docstring"""

    def 						a_     (			self       ):
         snake_case											=							tempfile.mkdtemp()

         snake_case											=							[
             '''[UNK]''',
             '''[CLS]''',
             '''[SEP]''',
             '''[PAD]''',
             '''[MASK]''',
             '''的''',
             '''价''',
             '''格''',
             '''是''',
             '''15''',
             '''便''',
             '''alex''',
             '''##andra''',
             '''，''',
             '''。''',
             '''-''',
             '''t''',
             '''shirt''',
         ]
         snake_case											=							os.path.join(self.tmpdirname     ,   VOCAB_FILES_NAMES['''vocab_file''']       )
         with open(self.vocab_file     ,   '''w'''     ,   encoding='''utf-8'''       ) as vocab_writer:
              vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]       )       )

         snake_case											=							{
             '''do_resize''': True,
             '''size''': {'''height''': 2_2_4, '''width''': 2_2_4},
             '''do_center_crop''': True,
             '''crop_size''': {'''height''': 1_8, '''width''': 1_8},
             '''do_normalize''': True,
             '''image_mean''': [0.4814_5466, 0.457_8275, 0.4082_1073],
             '''image_std''': [0.2686_2954, 0.2613_0258, 0.2757_7711],
             '''do_convert_rgb''': True,
         }
         snake_case											=							os.path.join(self.tmpdirname     ,   __snake_case       )
         with open(self.image_processor_file     ,   '''w'''     ,   encoding='''utf-8'''       ) as fp:
              json.dump(__snake_case     ,   __snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return BertTokenizer.from_pretrained(self.tmpdirname     ,   **__snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return BertTokenizerFast.from_pretrained(self.tmpdirname     ,   **__snake_case       )
    def 						a_     (			self     ,   **__snake_case       ):
         return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname     ,   **__snake_case       )
    def 						a_     (			self       ):
         shutil.rmtree(self.tmpdirname       )
    def 						a_     (			self       ):
         snake_case											=							[np.random.randint(2_5_5     ,   size=(3, 3_0, 4_0_0)     ,   dtype=np.uinta       )]

         snake_case											=							[Image.fromarray(np.moveaxis(__snake_case     ,   0     ,   -1       )       ) for x in image_inputs]

         return image_inputs
    def 						a_     (			self       ):
         snake_case											=							self.get_tokenizer()
         snake_case											=							self.get_rust_tokenizer()
         snake_case											=							self.get_image_processor()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )
         processor_slow.save_pretrained(self.tmpdirname       )
         snake_case											=							ChineseCLIPProcessor.from_pretrained(self.tmpdirname     ,   use_fast=__snake_case       )

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )
         processor_fast.save_pretrained(self.tmpdirname       )
         snake_case											=							ChineseCLIPProcessor.from_pretrained(self.tmpdirname       )

         self.assertEqual(processor_slow.tokenizer.get_vocab()     ,   tokenizer_slow.get_vocab()       )
         self.assertEqual(processor_fast.tokenizer.get_vocab()     ,   tokenizer_fast.get_vocab()       )
         self.assertEqual(tokenizer_slow.get_vocab()     ,   tokenizer_fast.get_vocab()       )
         self.assertIsInstance(processor_slow.tokenizer     ,   __snake_case       )
         self.assertIsInstance(processor_fast.tokenizer     ,   __snake_case       )

         self.assertEqual(processor_slow.image_processor.to_json_string()     ,   image_processor.to_json_string()       )
         self.assertEqual(processor_fast.image_processor.to_json_string()     ,   image_processor.to_json_string()       )
         self.assertIsInstance(processor_slow.image_processor     ,   __snake_case       )
         self.assertIsInstance(processor_fast.image_processor     ,   __snake_case       )
    def 						a_     (			self       ):
         snake_case											=							ChineseCLIPProcessor(tokenizer=self.get_tokenizer()     ,   image_processor=self.get_image_processor()       )
         processor.save_pretrained(self.tmpdirname       )

         snake_case											=							self.get_tokenizer(cls_token='''(CLS)'''     ,   sep_token='''(SEP)'''       )
         snake_case											=							self.get_image_processor(do_normalize=__snake_case       )

         snake_case											=							ChineseCLIPProcessor.from_pretrained(
             self.tmpdirname     ,   cls_token='''(CLS)'''     ,   sep_token='''(SEP)'''     ,   do_normalize=__snake_case       )

         self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer_add_kwargs.get_vocab()       )
         self.assertIsInstance(processor.tokenizer     ,   __snake_case       )

         self.assertEqual(processor.image_processor.to_json_string()     ,   image_processor_add_kwargs.to_json_string()       )
         self.assertIsInstance(processor.image_processor     ,   __snake_case       )
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							self.prepare_image_inputs()

         snake_case											=							image_processor(__snake_case     ,   return_tensors='''np'''       )
         snake_case											=							processor(images=__snake_case     ,   return_tensors='''np'''       )

         for key in input_feat_extract.keys():
              self.assertAlmostEqual(input_feat_extract[key].sum()     ,   input_processor[key].sum()     ,   delta=1E-2       )
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							'''Alexandra，T-shirt的价格是15便士。'''

         snake_case											=							processor(text=__snake_case       )

         snake_case											=							tokenizer(__snake_case       )

         for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key]     ,   encoded_processor[key]       )
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							'''Alexandra，T-shirt的价格是15便士。'''
         snake_case											=							self.prepare_image_inputs()

         snake_case											=							processor(text=__snake_case     ,   images=__snake_case       )

         self.assertListEqual(list(inputs.keys()       )     ,   ['''input_ids''', '''token_type_ids''', '''attention_mask''', '''pixel_values''']       )

         # test if it raises when no input is passed
         with pytest.raises(__snake_case       ):
              processor()
    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         snake_case											=							processor.batch_decode(__snake_case       )
         snake_case											=							tokenizer.batch_decode(__snake_case       )

         self.assertListEqual(__snake_case     ,   __snake_case       )




    def 						a_     (			self       ):
         snake_case											=							self.get_image_processor()
         snake_case											=							self.get_tokenizer()

         snake_case											=							ChineseCLIPProcessor(tokenizer=__snake_case     ,   image_processor=__snake_case       )

         snake_case											=							'''Alexandra，T-shirt的价格是15便士。'''
         snake_case											=							self.prepare_image_inputs()

         snake_case											=							processor(text=__snake_case     ,   images=__snake_case       )

         self.assertListEqual(list(inputs.keys()       )     ,   processor.model_input_names       )




